Computational Genome Analysis: An Introduction (Statistics for Biology and Health)
Written on 12:12 AM by மு.இரா
by Richard C. Deonier (Author), Simon Tavaré (Author), Michael S. Waterman (Author)
Computational Genome Analysis: An Introduction presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book is appropriate for a one-semester course for advanced undergraduate or beginning graduate students, and it can also introduce computational biology to computer scientists, mathematicians, or biologists who are extending their interests into this exciting field.
This book features:
Topics organized around biological problems, such as sequence alignment and assembly, DNA signals, analysis of gene expression, and human genetic variation
Presentation of fundamentals of probability, statistics, and algorithms
Implementation of computational methods with numerous examples based upon the R statistics package
Extensive descriptions and explanations to complement the analytical development
More than 100 illustrations and diagrams (some in color) to reinforce concepts and present key results from the primary literature
Exercises at the end of chapters
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